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Vijay Narayanan

Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference

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Jul 18, 2023
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AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing

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May 17, 2023
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Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators

Feb 16, 2023
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In-memory Realization of In-situ Few-shot Continual Learning with a Dynamically Evolving Explicit Memory

Jul 14, 2022
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Joint Coreset Construction and Quantization for Distributed Machine Learning

Apr 13, 2022
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A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays

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Apr 05, 2021
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Robust Coreset Construction for Distributed Machine Learning

Apr 11, 2019
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A Quantitative Evaluation Framework for Missing Value Imputation Algorithms

Nov 10, 2013
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